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Network Routing: Fundamentals, Applications, and Emerging Technologies

2014年

作者： Sudip Misra Sumit Goswami

ISBN: (数字)9781119029380;9781119029397

ISBN: (纸本)9780470750063

Network Routing: Fundamentals, Applications and Emerging Technologies serves as single point of reference for both advanced undergraduate and graduate students studying network routing, covering both the fundamental and more moderately advanced concepts of routing in traditional data networks such as the Internet, and emerging routing concepts currently being researched and developed, such as cellular networks, wireless ad hoc networks, sensor networks, and low power networks. Furthermore, QoS routing, and security and reliability are also discussed. Additionally, the book assesses the need for the different technologies, techniques and solutions for given problems in network routing, and provides model solutions. Apart for conventional network routing topics, certain sections in various chapters cover contemporary topics like challenges in mobile computing, interoperability and applications of low power wireless personal area network, network management, mobile agents, attack surface, tactical networks, and cognitive security. • Focuses on key concepts in different network technologies (e.g. the Internet, wireless ad hoc networks etc.)• Provides a single point of reference on network routing• Discusses techniques for given problems in network routing, and provides model solutions• Explores advanced concepts in network routing such as security and reliability and fault-tolerance• Includes an accompanying website containing PowerPoint slides and solutions to questions ***/go/misra2204 This book is unique. It deals with routing in multiple generations ofcommunication –from NSFNet to IoT, passing through ATM, MPLS, ad hoc, cellular, and wireless sensor networks in-between. This will clearly have a differentiating value for the readers. The technology is changing at an unprecedented pace, and the modern-day networks are significantly different from how they looked just a decade ago. This has resulted in numerous

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Overlapping Community Detection in social network based on Microblog User Model

Overlapping Community Detection in social network based on M...

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International Conference on Data science and Advanced Analytics (DSAA)

作者： Yajun Gu Bofeng Zhang Guobing Zou Mingqing Huang Keyuan Jiang School of Computer Engineering & Science Shanghai University Shanghai China Department of Computer Information Technology & Graphics Purdue University Calumet Indiana USA

Online social networks have found a significant increase in their popularity in recent years. All the networks have community structure, and one of the research problems mostly frequently tackled is the discovery of communities. An overlapping community is a network structure that allows one node to be a member of multiple communities. The method presented in this paper aims at detecting overlapping communities in social networks, and its novelty lies in that it combines with the Microblog User Model (MUM) which can reflect the interest of the user accurately. First, the MUM network, which is an undirected and weighted network, is constructed by computing the similarity among MUMs. Afterwords, Overlapping Community Detection based on MUM (OCD-MUM) is performed to partition the network. A community stops expanding when the fitness function reaches a local maximum. The communities detected are locally optimized. A user's interest is not only decided by the MUM, but it is also affected by the communities the user belongs to. The community model can reflect the interest of the community. The MUM is updated with community model of its communities, and therefore the interest of the user can be predicted by these communities. Our experiment result shows that OCD-MUM has a higher modularity Q value than traditional methods and the predicted interest is more close to the real world situations.

关键词： Communities Computational modeling Predictive models Social network services Image edge detection Vectors Clustering algorithms

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Exploring the effects of virtual machine placement on the transmission of infections in cloud

Exploring the effects of virtual machine placement on the tr...

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International Symposium on Telecommunications, IST

作者： Farzaneh Abazari Morteza Analoui School of Computer Engineering Iran University of Science and Technology Tehran Iran Associate Professor of Computer Engineering Iran University of Science and Technology Tehran Iran

Cloud Computing has recently emerged as a computing paradigm for delivering IT resources as services over the internet. However, there still exist significant problems with regard to secure delivery of services using Cloud-based IT resources. As long as malicious virtual machines could affect its host and other machines, the virtual machine placement is an important issues. In this paper, we outline an approach based on a combination of graph theory and agent based simulations to study epidemics in the cloud computing and control the transmission of infections. We present our results on the graph properties of virtual machines graph, as well as simulation-based dynamic analysis of infection spread in such networks. We identify a number of measures that are significant for understanding epidemics and for developing new strategies in virtual machines placement algorithm.

关键词： Virtual machining Virtualization Cloud computing Virtual machine monitors Mathematical model computer crime

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A new probability distribution for simultaneous representation of uncertain position and orientation

A new probability distribution for simultaneous representati...

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International Conference on Information Fusion

作者： Igor Gilitschenski Gerhard Kurz Simon J. Julier Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Karlsruhe Institute of Technology (KIT) Germany Department of Computer Science Virtual Environments and Computer Graphics Group

This work proposes a novel way to represent uncertainty on the Lie group of rigid-body motions in the plane. This is achieved by using dual quaternions for representation of a planar rigid-body motion and proposing a probability distribution from the exponential family of distributions that inherently respects the underlying structure of the representation. This is particularly beneficial in scenarios involving strong measurement noise. A relationship between the newly proposed distributional model and the Bingham distribution is discussed. The presented results involve formulas for computation of the normalization constant, the mode, parameter estimation techniques, and a closed-form Bayesian measurement fusion.

关键词： Quaternions Estimation Vectors Transmission line matrix methods Probability distribution Bayes methods Robot sensing systems

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Image-based X-ray visualization techniques for spatial understanding in outdoor augmented reality 14

Image-based X-ray visualization techniques for spatial under...

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26th Australian computer-Human Interaction Conference, OzCHI 2014

作者： Zollmann, Stefanie Grasset, Raphael Reitmayr, Gerhard Langlotz, Tobias Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Animation Research Ltd. Dunedin New Zealand Qualcomm Austria Research Center Vienna Austria Department of Information Science University of Otago Dunedin New Zealand

ISBN: (纸本)9781450306539

This paper evaluates different state-of-the-art approaches for implementing an X-ray view in Augmented Reality (AR). Our focus is on approaches supporting a better scene understanding and in particular a better sense of depth order between physical objects and digital objects. One of the main goals of this work is to provide effective X-ray visualization techniques that work in unprepared outdoor environments. In order to achieve this goal, we focus on methods that automatically extract depth cues from video images. The extracted depth cues are combined in ghosting maps that are used to assign each video image pixel a transparency value to control the overlay in the AR view. Within our study, we analyze three different types of ghosting maps, 1) alpha-blending which uses a uniform alpha value within the ghosting map, 2) edge-based ghosting which is based on edge extraction and 3) image-based ghosting which incorporates perceptual grouping, saliency information, edges and texture details. Our study results demonstrate that the latter technique helps the user to understand the subsurface location of virtual objects better than using alpha-blending or the edge-based ghosting. Copyright 2014 ACM.

关键词： Augmented reality

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RFA-Cut: Semi-automatic Segmentation of Radiofrequency Ablation Zones with and without Needles via Optimal s-t-Cuts

RFA-Cut: Semi-automatic Segmentation of Radiofrequency Ablat...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Jan Egger Harald Busse Philipp Brandmaier Daniel Seider Matthias Gawlitza Steffen Strocka Philip Voglreiter Mark Dokter Michael Hofmann Bernhard Kainz Xiaojun Chen Alexander Hann Pedro Boechat Wei Yu Bernd Freisleben Tuomas Alhonnoro Mika Pollari Michael Moche Dieter Schmalstieg Institute for Computer Graphics and Vision Graz University of Technology Austria Dept. of Diagnostic and Interventional Radiology Leipzig University Hospital Germany Dept. of Computing Imperial College London UK School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China Dept. of Internal Medicine and Gastroenterology Katharinenhospital Stuttgart Germany Distributed Systems Group Philipp University of Marburg Germany School of Science Aalto University Espoo Finland

ISBN: (纸本)9781424492695

In this contribution, we present a semi-automatic segmentation algorithm for radiofrequency ablation (RFA) zones via optimal s-t-cuts. Our interactive graph-based approach builds upon a polyhedron to construct the graph and was specifically designed for computed tomography (CT) acquisitions from patients that had RFA treatments of Hepatocellular Carcinomas (HCC). For evaluation, we used twelve post-interventional CT datasets from the clinical routine and as evaluation metric we utilized the Dice Similarity Coefficient (DSC), which is commonly accepted for judging computer aided medical segmentation tasks. Compared with pure manual slice-by-slice expert segmentations from interventional radiologists, we were able to achieve a DSC of about eighty percent, which is sufficient for our clinical needs. Moreover, our approach was able to handle images containing (DSC=75.9%) and not containing (78.1%) the RFA needles still in place. Additionally, we found no statistically significant difference (p<0.423) between the segmentation results of the subgroups for a Mann-Whitney test. Finally, to the best of our knowledge, this is the first time a segmentation approach for CT scans including the RFA needles is reported and we show why another state-of-the-art segmentation method fails for these cases. Intraoperative scans including an RFA probe are very critical in the clinical practice and need a very careful segmentation and inspection to avoid under-treatment, which may result in tumor recurrence (up to 40%). If the decision can be made during the intervention, an additional ablation can be performed without removing the entire needle. This decreases the patient stress and associated risks and costs of a separate intervention at a later date. Ultimately, the segmented ablation zone containing the RFA needle can be used for a precise ablation simulation as the real needle position is known.

关键词： RFA decreases patient stress

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Noise removal using First Order Neighborhood Mean Filter

Noise removal using First Order Neighborhood Mean Filter

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Conference on IT in Business, Industry and Government (CSIBIG)

作者： Priyanka Shrivastava Uday Pratap Singh Assistam Professor Computer Science Department Lakshmi Narain College of Technology Bhopal India

A numbers of algorithms have been proposed for the removal of fixed valued impulse noise (salt and pepper) from highly corrupted gray scale and color images, but they failed to give better results at high noise densities. This paper is designed in accordance with the proposed algorithm to get better result at high noise density levels. The proposed algorithm works on two steps for de-noising the image first step is to detect that the pixel is noisy or not and the second step is the replacement of that noisy pixel. The proposed algorithm considers first order neighborhood pixels for detecting the noisy pixel and mean filter is considered. Color images are also de-noised by extracting the R, G and B pixels from noisy image and then they are de-noised separately and then merged together to again form the color image. Proposed algorithm is compared with all other standard and well known algorithms and found to have good noise removal capabilities at high densities. This algorithm shows better results than Median Filter (MF), Adaptive Median Filter (AMF), Progressive Switched Median Filter (PSMF), Decision Based Algorithm (DBA), Modified Decision Based Algorithm (MDBA), Modified Decision Based Unsymmetrical Trimmed Median Filter (MDBUTMF), and Modified Non-Linear Filter (MNF). Different grayscale and color images are tested by using the algorithm and it gave better Peak Signal Noise Ratio (PSNR) and Image Enhancement Factor (IEF) at low, medium and high noise densities.

关键词： Noise Color Sensors Image sensors

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Clustering Software Components for Program Restructuring and Component Reuse Using Hybrid XNOR Similarity Function

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Procedia technology 2014年 12卷 246-254页

作者： Chintakindi Srinivas Vangipuram Radhakrishna C.V. Guru Rao Associate Professor of CSE Kakatiya Institute of Technology and Science Warangal INDIA Department of Information Technology VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad INDIA Professor of Computer Science and Engineering SR Engineering CollegeWarangal INDIA

Component based software development has gained a lot of practical importance in the field of software engineering from academic researchers and also from industry perspective. Finding components for efficient software reuse is one of the important problems aimed by researchers. Clustering reduces the search space of components by grouping similar entities together thus ensuring reduced time complexity as it reduces the search time for component retrieval. In this research, we instigate a generalized approach for clustering a given set of documents or software components by defining a similarity function called hybrid XNOR function to find degree of similarity between two document sets or software components. A similarity matrix is obtained for a given set of documents or components by applying hybrid XNOR function. We define and design the algorithm for component or document clustering which has the input as similarity matrix and output being set of clusters. The output is a set of highly cohesive pattern groups or components.

关键词： clustering similarity frequent item mining classification component

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Feedback-based smartphone strategic sampling for BYOD security

Feedback-based smartphone strategic sampling for BYOD securi...

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International Conference on computer Communications and Networks (ICCCN)

作者： Feng Li Chin-Tser Huang Jie Huang Wei Peng Department of Computer Information and Graphics Technology Department of Computer and Information Science Indiana University-Purdue University Indianapolis Indianapolis IN U.S.A. Department of Computer Science and Engineering University of South Carolina Columbia SC U.S.A.

ISBN: (纸本)9781479935734

Bring Your Own Device (BYOD) is an information technology (IT) policy that allows employees to use their own wireless devices to access internal network at work. Mobile malware is a major security concern that impedes BYOD's further adoption in enterprises. Existing works identify the need for better BYOD security mechanisms that balance between the strength of such mechanisms and the costs of implementing such mechanisms. In this paper, based on the idea of self-reinforced feedback loop, we propose a periodic smartphone sampling mechanism that significantly improve BYOD security mechanism's effectiveness without incurring further costs. We quantify the likelihood that “a BYOD smartphone is infected by malware” by two metrics, vulnerability and uncertainty, and base the iterative sampling process on these two metrics; the updated values of these metrics are fed back into future rounds of the mechanism to complete the feedback loop. We validate the efficiency and effectiveness of the proposed strategic sampling via simulations driven by publicly available, real-world collected traces.

关键词： Malware Measurement Uncertainty Topology Wireless communication Feedback loop

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A New Scheme for Trajectory Visualization

A New Scheme for Trajectory Visualization

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International Conference on Information Visualisation (IV)

作者： Yuejun Guo Qing Xu Xiu Li Xiaoxiao Luo Mateu Sbert School of Computer Science and Technology Tianjin University Tianjin China Graphics and Imaging Laboratory Universitat de Girona Girona Spain

This paper proposes a new approach for trajectory clustering and visualization. During clustering, speed and direction are both taken into account as the important properties of a trajectory. Additionally, the temporal change of the trajectories is explicitly considered in the procedure of clustering. Importantly, we introduce the uncertainty to represent the homogeneity of the updating trajectories based on their speed and direction attributes, to help observe and understand the happening of the trajectory data. Finally, based on the use of the HSV color space, we devise three patterns for graphically presenting the trajectory data in different perspectives. Namely, 'H+S' visualizes the clustered trajectories emphasizing the speed attribute of them. 'H+S+Update' depicts more information on the "latest" trajectory data, compared with the results by 'H+S'. 'H+V+Update' explicitly presents the uncertainty of the trajectory data. Our approach has shown its potential for the effective trajectory analysis.

关键词： Trajectory Uncertainty Visualization Data visualization Image color analysis Clustering algorithms Aircraft

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